Remember when a toothbrush just cleaned your teeth? Now it's 'AI-powered' because apparently, we need machine learning to tell us we're brushing too hard on our molars. Welcome to 2026, where everything from cat translation apps to virtual meeting attendants requires a neural network. The Irish Times recently explored the question everyone's been too afraid to ask directly: how much AI is actually too damn much?

Gen Z Is Over It (And They Have Data to Prove It)

Here's the uncomfortable truth Big Tech doesn't want on its investor slides: younger users are actively frustrated with generative AI, not thrilled by it. A Gallup report published in April found that while roughly half of Gen Z users reported using generative AI tools, nearly one-third said the technology made them feel angry. Not excited. Not liberated. Angry. The much-hyped productivity utopia promised by OpenAI, Anthropic, and their VC-backed ilk is landing like a broken software update—complicated, invasive, and somehow making daily life worse instead of better.

The Hiring Nightmare Loop Nobody Asked For

The job market has become the perfect case study for AI's absurdity. Candidates are using AI to write cover letters and polish resumes because, let's face it, nobody reads them anyway. Meanwhile, hiring managers have outsourced first-round screening to AI systems that parse keywords like resume-parsing robots from 2005—but now with hallucination problems. You get AI screening AI-generated applications, creating a feedback loop that would make any engineer wince. Candidates can't escape it, and employers think they're being efficient while missing every human signal that actually predicts job performance. This isn't innovation—it's automation theater.

Trust Issues All the Way Down

Anthropic's Claude chatbot once offered this gem when asked about AI neutrality: 'AI is not neutral. It is built by humans, trained on our data, and open to every bias, blind spot, and commercial interest of those behind it.' When we use AI blindly, we're not removing human judgment from the equation—we're just making that judgment invisible and unaccountable. This philosophy should be tattooed on every product manager's forearm before they slap 'AI-powered' on their latest gadget.

The Musk vs OpenAI Spectacle (Because Of Course)

If you wanted proof that AI governance is a mess, look no further than Elon Musk's failed lawsuit against OpenAI and Sam Altman. Musk accused the company of abandoning its nonprofit mission to benefit humanity in favor of enriching investors—then spent part of his legal energy posting on X about space exploration and Tommy Robinson updates while building his own AI startup with 'accelerate human scientific discovery' messaging. The case revealed internal drama involving Mira Murati, Altman's brief ousting in 2023, and a portrait of corporate leadership that wouldn't inspire confidence in anyone paying attention. Musk lost, but not before dragging plenty of people through the mud publicly.

Regulators Are Starting to Notice

The UK competition regulator recently forced Google to allow publishers opt-out from AI summaries—acknowledging that training these systems on human-created content without consent is a problem worth addressing. European authorities are considering stricter copyright rules that could make it harder for AI companies to operate competitively in the region. The free ride might be ending, and that's probably long overdue.

Key Takeaways

  • Gen Z isn't buying the AI hype: Nearly one-third of younger users report anger at generative AI despite half using it regularly
  • Hiring has become an AI-powered feedback loop where nobody wins
  • 'AI is not neutral'—trust issues stem from invisible human bias baked into systems
  • Legal battles like Musk vs OpenAI expose how messy AI governance actually is
  • UK and EU regulators are finally pushing back on training data practices

The Bottom Line

The tech industry spent years convincing us that more AI in everything was progress. Now Gen Z—the exact demographic these companies need to survive—is actively irritated by the technology, and courts are revealing the trust issues we always suspected were hiding under the hype. Maybe the real innovation isn't building more AI products. It's knowing when NOT to build them.